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James J. Okarimia - Aligning Finance, Risk and Data Analytics in Meeting
the Requirements of Emerging Regulations
Banks must meet more (and more varied) regulations today than ever. The sheer
scale and scope of banking regulations, including Dodd-Frank, Basel III and IFRS,
pose challenges to all financial institutions, from the smallest bank to the largest
financial services enterprise.
Financial organizations must keep regulatory requirements top of mind, since failing to meet these rules and
regulations places banks in a precarious position. Potential fines and remedial actions that result from noncompliance
are only part of the risk. Financial institutions also face significant business consequences if they fail to take the
necessary steps to meet regulations.
The increasing number of regulations and their widening scope were enacted to protect bank depositors and
customers, but they were also put in place to protect financial institutions and ensure their viability. The current
regulatory framework aims to make banks and banking systems more resilient and stable. While ensuring that their
technology enables the necessary transparency, analytics and reporting for regulatory compliance, financial
institutions can also improve operational inefficiency, hone their competitive advantage and mitigate myriad risks.
The Big 3: Compliance Requirements
A common theme in regulations such as Dodd-Frank, Basel III and IFRS is greater transparency or documentation
for what financial institutions are doing today. These regulations make it necessary for financial firms to create
information to meet compliance, and savvy financial institutions are beginning to realize that the same information
can help them run their businesses better and make better and more informed decisions.
To comply with these and other regulatory mandates, financial firms must transform their IT infrastructure. By
updating and streamlining the old ways of doing things to comply with regulations, banks can also sharpen their
ability to act on and profit from market opportunities.
Meeting regulatory compliance and improving business decisions are both fundamentally data challenges. Those
institutions that master their management of data and information stand to benefit on both fronts.
Meeting the New Requirements
Raising the quality, consistency and transparency of capital as required by the Dodd-Frank Act is driving financial
firms to collect, analyze and report more detailed data to regulators, auditors, management and customers. To meet
these requirements, financial firms need to address not only capital adequacy, but also mortgages, liquidity, stress
testing and other provisions that will challenge the need to establish real-time visibility, analysis and reporting of
enterprise wide data. To do so, many financial organizations will need to transform their existing IT infrastructure.
But reacting to regulations on a rule-by-rule basis isn’t a viable strategy. Instead, financial firms must come up with a
well-designed plan to transform their IT infrastructure and operations to provide visibility, analytics and reporting
necessary to meet current — and future — mandates. Some organizations are aggressively consolidating their
systems, seeing the need for regulatory compliance as an opportunity to fix systems that may not be working
optimally. An optimal IT infrastructure can help institutions drive down both the time and cost of maintaining
regulatory compliance and, at the same time, enable these firms to expand resources, expertise, intelligence and
visibility across the enterprise.
To ensure compliance, financial institutions require an IT infrastructure that will normalize data to enable:
• A logical data model based on deep domain experience
• An end-use driven and predefined physical data model for sourcing and provisioning, ready for immediate
deployment and use across the enterprise
• A unified and conforming reporting data model to perform fast queries across all functional domains
• Shared data, metadata, computations, calculations, business rules and controlled access that enable organizations
to meet emerging or changing cross-functional business and regulatory mandates quickly and with reduced expense
• Thousands of prebuilt data quality checks contextualized to the institution’s analytical end use that enable financial
institutions to eliminate accuracy and consistency issues
• A formal and centralized general ledger reconciliation process, for accurate and fully auditable reporting that
eliminates inconsistencies across ledgers, books and marts
Analytical requirements are dramatically increasing. Financial firms must capture and analyze more data than ever before, in 
chunks that are close to a terabyte. Moving this scale and scope of data around in a network is no longer practical; running 
applications in memory inside the database is becoming the preferred strategy. 
• The capability to handle high volume, what-if computations across business domains to support enterprise-
level stress testing and scenario analysis
• Analytical applications that can combine results from multiple business areas to easily and securely
support cross-functional analytics throughout the enterprise
• A self-service business intelligence environment with all key business dimensions and vocabulary prebuilt
to help users get answers quickly and efficiently
• Fast query response when performing time-sensitive ad hoc analytics and reporting
• Consolidation of data across business lines to help reduce the IT footprint and the total cost of ownership 
Unifying the Core Platform
CIOs and CTOs today are typically charged with helping business make better purchasing decisions. Banks and
financial services companies have traditionally acquired technology in a reactionary way, implementing solutions
such as market risk systems or credit risk systems to address an acute problem. Over the years, financial services
organizations can wind up with dozens of disparate systems from dozens of different vendors, all acquired at a time
of need. This disparity, however, creates massive problems.
If a firm has 30 different systems, each providing the firm with information on different time horizons, on different time
frames and on top of different data, the organization won’t be able to reconcile the information to create a single view
of the organization. In a competitive operating environment, it’s essential to have a holistic, enterprise wide view that
makes it possible to drill down into the lines of business or different product or asset types. Consolidating these
disparate pieces into a single system is a practical means to get this essential holistic view.
Under the audit and transparency data governance requirements, regulators need to see how the data came in, how
it came together and what rules were used to clean, scrub and transform the data. Financial organizations must show
how they do the quantitative steps, as well as how data landed in a reporting area. Organizations that have dozens of
disparate, siloes systems will find it difficult — if not impossible — to be able to show end-to-end flow and continuity.
The diverse array of different tools from different vendors results in complicated support issues as well. If a bank is
dealing with 300 vendors, renegotiating contracts becomes time-consuming
and costly. If the institution can pare down the number of technology vendors to 20, it stands to save a significant
amount of time and money.
Piecemeal technology acquisition also creates integration headaches. As an organizations’ IT environment becomes
more complex, the integration challenges only get more complicated and costly. In the long run, integration isn’t
sustainable.
Having a common platform facilitates the introduction of new products and services, which can make a huge difference in a 
competitive marketplace. Integrating a new offering is as simple as dropping in the new functionality when everything is on 
the same platform and data model. IT can support business and respond to ever‐changing market conditions much more 
quickly. 
Four Steps to IT Transformation
Creating and implementing an IT transformation initiative to help meet regulatory compliance can be a daunting
proposition. However, financial firms can get started with four steps:
1. Obtain IT transformation expertise and resources. Financial firms must identify internal personnel with the
experience, skills and time necessary to plan and manage the transformation, hire more staff or turn to a third-party
outsourcing relationship for the needed expertise.
2. Firms must define their IT transformation strategy, garnering support from management. The strategy must
include a balanced allocation of funding for personnel and tools.
3. Financial organizations must implement an automated and intelligent real-time analytical infrastructure.
This should consist of a business intelligence platform, analytical computations and a unified financial services model.
4. Organizations must establish a baseline for data and anticipated activity. Dodd- Frank requires institutions to
enable their businesses to perform complex what-if scenarios and enterprise-level analytics. Banks must be able to
simultaneously provide fast query response for time-sensitive ad hoc analytics and reporting, and also to cut oper-
ating costs by combining siloed functional warehouses across business lines. This can be accomplished by
centralizing all relevant data to empower the organization’s personnel to efficiently enter information or automatically
gather the information and then store it in a database for high-performance data warehousing and online transaction
processing.
Financial services organizations must be proactive in taking steps to comply with regulatory mandates. A sensible,
comprehensive approach to industry and government mandates gives banks the opportunity to transform their IT
infrastructure, improving not only regulatory compliance, but also operational efficiency and competitive positioning. ■
 
A publication by James Jeffrey Okarimia 
Managing Partner at RM associates 
Partners in Enterprise Risk Managements 
 

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Aligning Finance, Risk and Data for Regulatory Compliance

  • 1. James J. Okarimia - Aligning Finance, Risk and Data Analytics in Meeting the Requirements of Emerging Regulations Banks must meet more (and more varied) regulations today than ever. The sheer scale and scope of banking regulations, including Dodd-Frank, Basel III and IFRS, pose challenges to all financial institutions, from the smallest bank to the largest financial services enterprise. Financial organizations must keep regulatory requirements top of mind, since failing to meet these rules and regulations places banks in a precarious position. Potential fines and remedial actions that result from noncompliance are only part of the risk. Financial institutions also face significant business consequences if they fail to take the necessary steps to meet regulations. The increasing number of regulations and their widening scope were enacted to protect bank depositors and customers, but they were also put in place to protect financial institutions and ensure their viability. The current regulatory framework aims to make banks and banking systems more resilient and stable. While ensuring that their technology enables the necessary transparency, analytics and reporting for regulatory compliance, financial institutions can also improve operational inefficiency, hone their competitive advantage and mitigate myriad risks. The Big 3: Compliance Requirements A common theme in regulations such as Dodd-Frank, Basel III and IFRS is greater transparency or documentation for what financial institutions are doing today. These regulations make it necessary for financial firms to create information to meet compliance, and savvy financial institutions are beginning to realize that the same information can help them run their businesses better and make better and more informed decisions. To comply with these and other regulatory mandates, financial firms must transform their IT infrastructure. By updating and streamlining the old ways of doing things to comply with regulations, banks can also sharpen their ability to act on and profit from market opportunities. Meeting regulatory compliance and improving business decisions are both fundamentally data challenges. Those institutions that master their management of data and information stand to benefit on both fronts. Meeting the New Requirements Raising the quality, consistency and transparency of capital as required by the Dodd-Frank Act is driving financial firms to collect, analyze and report more detailed data to regulators, auditors, management and customers. To meet these requirements, financial firms need to address not only capital adequacy, but also mortgages, liquidity, stress testing and other provisions that will challenge the need to establish real-time visibility, analysis and reporting of enterprise wide data. To do so, many financial organizations will need to transform their existing IT infrastructure. But reacting to regulations on a rule-by-rule basis isn’t a viable strategy. Instead, financial firms must come up with a well-designed plan to transform their IT infrastructure and operations to provide visibility, analytics and reporting necessary to meet current — and future — mandates. Some organizations are aggressively consolidating their systems, seeing the need for regulatory compliance as an opportunity to fix systems that may not be working optimally. An optimal IT infrastructure can help institutions drive down both the time and cost of maintaining regulatory compliance and, at the same time, enable these firms to expand resources, expertise, intelligence and visibility across the enterprise. To ensure compliance, financial institutions require an IT infrastructure that will normalize data to enable: • A logical data model based on deep domain experience
  • 2. • An end-use driven and predefined physical data model for sourcing and provisioning, ready for immediate deployment and use across the enterprise • A unified and conforming reporting data model to perform fast queries across all functional domains • Shared data, metadata, computations, calculations, business rules and controlled access that enable organizations to meet emerging or changing cross-functional business and regulatory mandates quickly and with reduced expense • Thousands of prebuilt data quality checks contextualized to the institution’s analytical end use that enable financial institutions to eliminate accuracy and consistency issues • A formal and centralized general ledger reconciliation process, for accurate and fully auditable reporting that eliminates inconsistencies across ledgers, books and marts Analytical requirements are dramatically increasing. Financial firms must capture and analyze more data than ever before, in  chunks that are close to a terabyte. Moving this scale and scope of data around in a network is no longer practical; running  applications in memory inside the database is becoming the preferred strategy.  • The capability to handle high volume, what-if computations across business domains to support enterprise- level stress testing and scenario analysis • Analytical applications that can combine results from multiple business areas to easily and securely support cross-functional analytics throughout the enterprise • A self-service business intelligence environment with all key business dimensions and vocabulary prebuilt to help users get answers quickly and efficiently • Fast query response when performing time-sensitive ad hoc analytics and reporting • Consolidation of data across business lines to help reduce the IT footprint and the total cost of ownership  Unifying the Core Platform CIOs and CTOs today are typically charged with helping business make better purchasing decisions. Banks and financial services companies have traditionally acquired technology in a reactionary way, implementing solutions such as market risk systems or credit risk systems to address an acute problem. Over the years, financial services organizations can wind up with dozens of disparate systems from dozens of different vendors, all acquired at a time of need. This disparity, however, creates massive problems. If a firm has 30 different systems, each providing the firm with information on different time horizons, on different time frames and on top of different data, the organization won’t be able to reconcile the information to create a single view of the organization. In a competitive operating environment, it’s essential to have a holistic, enterprise wide view that makes it possible to drill down into the lines of business or different product or asset types. Consolidating these disparate pieces into a single system is a practical means to get this essential holistic view. Under the audit and transparency data governance requirements, regulators need to see how the data came in, how it came together and what rules were used to clean, scrub and transform the data. Financial organizations must show how they do the quantitative steps, as well as how data landed in a reporting area. Organizations that have dozens of disparate, siloes systems will find it difficult — if not impossible — to be able to show end-to-end flow and continuity. The diverse array of different tools from different vendors results in complicated support issues as well. If a bank is dealing with 300 vendors, renegotiating contracts becomes time-consuming and costly. If the institution can pare down the number of technology vendors to 20, it stands to save a significant amount of time and money. Piecemeal technology acquisition also creates integration headaches. As an organizations’ IT environment becomes more complex, the integration challenges only get more complicated and costly. In the long run, integration isn’t sustainable. Having a common platform facilitates the introduction of new products and services, which can make a huge difference in a  competitive marketplace. Integrating a new offering is as simple as dropping in the new functionality when everything is on  the same platform and data model. IT can support business and respond to ever‐changing market conditions much more  quickly.  Four Steps to IT Transformation Creating and implementing an IT transformation initiative to help meet regulatory compliance can be a daunting proposition. However, financial firms can get started with four steps: 1. Obtain IT transformation expertise and resources. Financial firms must identify internal personnel with the experience, skills and time necessary to plan and manage the transformation, hire more staff or turn to a third-party outsourcing relationship for the needed expertise. 2. Firms must define their IT transformation strategy, garnering support from management. The strategy must include a balanced allocation of funding for personnel and tools.
  • 3. 3. Financial organizations must implement an automated and intelligent real-time analytical infrastructure. This should consist of a business intelligence platform, analytical computations and a unified financial services model. 4. Organizations must establish a baseline for data and anticipated activity. Dodd- Frank requires institutions to enable their businesses to perform complex what-if scenarios and enterprise-level analytics. Banks must be able to simultaneously provide fast query response for time-sensitive ad hoc analytics and reporting, and also to cut oper- ating costs by combining siloed functional warehouses across business lines. This can be accomplished by centralizing all relevant data to empower the organization’s personnel to efficiently enter information or automatically gather the information and then store it in a database for high-performance data warehousing and online transaction processing. Financial services organizations must be proactive in taking steps to comply with regulatory mandates. A sensible, comprehensive approach to industry and government mandates gives banks the opportunity to transform their IT infrastructure, improving not only regulatory compliance, but also operational efficiency and competitive positioning. ■   A publication by James Jeffrey Okarimia  Managing Partner at RM associates  Partners in Enterprise Risk Managements